Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "226"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 226 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 26 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 26 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 226, Node N19:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460009 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.835170 17.029317 -0.602647 0.611340 -1.174318 3.064859 -1.101943 0.022291 0.5757 0.5180 0.3481 nan nan
2460008 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.399527 25.445202 -0.671406 0.698498 -0.708343 3.302006 -0.791690 1.060792 0.6154 0.5397 0.3159 nan nan
2460007 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.424844 19.997539 -0.722614 0.321641 -1.175862 3.662212 -0.954283 -0.448402 0.5802 0.4934 0.3322 nan nan
2459999 RF_ok 0.00% 0.00% 0.00% 0.00% - - nan nan nan nan nan nan nan nan 0.6083 0.5220 0.2956 nan nan
2459998 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.562572 19.695243 -0.570773 0.361409 -0.954953 3.843095 -0.895579 -0.738267 0.5900 0.4923 0.3580 nan nan
2459997 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.637282 21.335782 -0.371519 0.432474 -0.957920 4.238126 -0.849737 -0.374144 0.6024 0.5052 0.3602 nan nan
2459996 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.563602 22.265974 -0.672788 0.412051 -1.222613 3.497436 -0.717497 2.097121 0.6116 0.5091 0.3763 nan nan
2459995 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.406073 21.202355 -0.643061 0.504741 -1.170337 3.171971 -0.794492 1.463475 0.6058 0.5157 0.3609 nan nan
2459994 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.478240 22.955043 -0.480862 0.394969 -1.078383 3.543245 -0.779049 -0.453519 0.6005 0.5033 0.3563 nan nan
2459993 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.199725 26.264594 -0.231440 0.688912 -1.058274 4.605910 -0.912778 0.138891 0.5868 0.4888 0.3621 nan nan
2459991 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.336984 26.887581 -0.351066 0.722475 -1.046229 3.796161 -0.814520 0.043682 0.5949 0.4961 0.3760 nan nan
2459990 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.134895 21.220133 -0.367262 0.945845 -0.940402 3.896177 -0.930583 0.075700 0.5961 0.5130 0.3697 nan nan
2459989 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.267939 19.791117 -0.131225 0.836683 -0.923488 2.825909 -0.937644 -1.038987 0.5962 0.5405 0.3662 nan nan
2459988 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.315632 12.896956 -0.421049 1.283487 -1.247340 6.758702 -0.751604 3.377240 0.5982 0.5674 0.3710 nan nan
2459987 RF_ok 0.00% 0.00% 0.00% 0.00% - - -0.477379 0.201413 -0.466187 0.994869 -1.038268 0.847172 -0.666312 -0.799203 0.6002 0.6228 0.3829 nan nan
2459986 RF_ok 0.00% 0.00% 0.00% 0.00% - - -0.419474 1.072737 -0.491289 1.316893 -1.057271 2.481548 -1.043167 1.298378 0.6293 0.6454 0.3332 nan nan
2459985 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.440444 3.902791 -0.532844 0.903417 -1.331823 3.444734 -1.151125 12.621327 0.6060 0.6033 0.3761 nan nan
2459984 RF_ok 0.00% 0.00% 0.00% 0.00% - - -0.544709 0.209577 -0.522301 0.997787 -1.163400 1.046865 -0.651758 -0.378735 0.6199 0.6423 0.3661 nan nan
2459983 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.600400 21.381331 -0.474830 0.855240 -1.452241 3.620349 -1.017142 0.526091 0.6235 0.5687 0.3098 nan nan
2459982 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.482918 16.485067 -0.825105 0.144865 -0.913159 0.707173 -1.139890 0.281927 0.6926 0.6100 0.2741 nan nan
2459981 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.720591 19.207009 -0.395437 1.275558 -0.993001 4.483264 -0.968910 2.783609 0.6040 0.5332 0.3628 nan nan
2459980 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.714285 20.025315 -0.669322 0.522042 -1.488004 3.290562 -1.207924 0.658327 0.6524 0.5785 0.2898 nan nan
2459979 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.613544 19.325818 -0.548433 0.635855 -1.052850 5.066180 -0.778055 -0.055865 0.5965 0.5317 0.3621 nan nan
2459978 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.567025 18.001313 -0.462638 0.877758 -0.773642 6.824068 -0.627410 1.261541 0.5982 0.5392 0.3701 nan nan
2459977 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.432814 19.173599 -0.555816 0.555906 -1.091637 3.764343 -1.076214 1.250102 0.5616 0.4894 0.3282 nan nan
2459976 RF_ok 100.00% 0.00% 0.00% 0.00% - - -0.668232 22.568866 -0.620542 0.659792 -1.104343 4.158627 -0.565073 -0.068657 0.6072 0.5175 0.3530 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 226: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 17.029317 -0.835170 17.029317 -0.602647 0.611340 -1.174318 3.064859 -1.101943 0.022291

Antenna 226: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 25.445202 25.445202 -0.399527 0.698498 -0.671406 3.302006 -0.708343 1.060792 -0.791690

Antenna 226: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 19.997539 -0.424844 19.997539 -0.722614 0.321641 -1.175862 3.662212 -0.954283 -0.448402

Antenna 226: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 226: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 19.695243 -0.562572 19.695243 -0.570773 0.361409 -0.954953 3.843095 -0.895579 -0.738267

Antenna 226: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 21.335782 -0.637282 21.335782 -0.371519 0.432474 -0.957920 4.238126 -0.849737 -0.374144

Antenna 226: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 22.265974 -0.563602 22.265974 -0.672788 0.412051 -1.222613 3.497436 -0.717497 2.097121

Antenna 226: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 21.202355 -0.406073 21.202355 -0.643061 0.504741 -1.170337 3.171971 -0.794492 1.463475

Antenna 226: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 22.955043 -0.478240 22.955043 -0.480862 0.394969 -1.078383 3.543245 -0.779049 -0.453519

Antenna 226: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 26.264594 -0.199725 26.264594 -0.231440 0.688912 -1.058274 4.605910 -0.912778 0.138891

Antenna 226: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 26.887581 -0.336984 26.887581 -0.351066 0.722475 -1.046229 3.796161 -0.814520 0.043682

Antenna 226: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 21.220133 21.220133 -0.134895 0.945845 -0.367262 3.896177 -0.940402 0.075700 -0.930583

Antenna 226: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 19.791117 19.791117 -0.267939 0.836683 -0.131225 2.825909 -0.923488 -1.038987 -0.937644

Antenna 226: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 12.896956 12.896956 -0.315632 1.283487 -0.421049 6.758702 -1.247340 3.377240 -0.751604

Antenna 226: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Power 0.994869 -0.477379 0.201413 -0.466187 0.994869 -1.038268 0.847172 -0.666312 -0.799203

Antenna 226: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Temporal Variability 2.481548 1.072737 -0.419474 1.316893 -0.491289 2.481548 -1.057271 1.298378 -1.043167

Antenna 226: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Temporal Discontinuties 12.621327 3.902791 -0.440444 0.903417 -0.532844 3.444734 -1.331823 12.621327 -1.151125

Antenna 226: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Temporal Variability 1.046865 -0.544709 0.209577 -0.522301 0.997787 -1.163400 1.046865 -0.651758 -0.378735

Antenna 226: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 21.381331 -0.600400 21.381331 -0.474830 0.855240 -1.452241 3.620349 -1.017142 0.526091

Antenna 226: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 16.485067 -0.482918 16.485067 -0.825105 0.144865 -0.913159 0.707173 -1.139890 0.281927

Antenna 226: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 19.207009 19.207009 -0.720591 1.275558 -0.395437 4.483264 -0.993001 2.783609 -0.968910

Antenna 226: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 20.025315 20.025315 -0.714285 0.522042 -0.669322 3.290562 -1.488004 0.658327 -1.207924

Antenna 226: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 19.325818 -0.613544 19.325818 -0.548433 0.635855 -1.052850 5.066180 -0.778055 -0.055865

Antenna 226: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 18.001313 18.001313 -0.567025 0.877758 -0.462638 6.824068 -0.773642 1.261541 -0.627410

Antenna 226: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 19.173599 -0.432814 19.173599 -0.555816 0.555906 -1.091637 3.764343 -1.076214 1.250102

Antenna 226: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
226 N19 RF_ok nn Shape 22.568866 22.568866 -0.668232 0.659792 -0.620542 4.158627 -1.104343 -0.068657 -0.565073
In [ ]: